Today's security systems usually fall into one of two categories: man or machine. So called "analyst driven solutions" rely on rules created by human experts and therefore miss any attacks that don't match the rules. Meanwhile, today's machine learning approaches rely on "anomaly detection," which tends to trigger false positives that both create distrust of the system and end up having to be investigated by humans, anyway. But what if there was a solution that could merge those two worlds? What would it look like?

Artificial intelligence (AI) developed at the Massachusetts Institute of Technology (MIT) can already detect 85pc of cyberattacks and is getting smarter every day, according to the institute. Scientists at MIT's prestigious Computer Science and Artificial Intelligence Lab (CSAIL) have developed AI that they believe can create a line of defence against the numerous cyberattacks that have crippled government agencies, health insurers and many others. And they have also claimed that their AI can detect attacks on networks as they happen 85pc of the time. 'That human-machine interaction creates a beautiful, cascading effect' – KALYAN VEERAMACHANENI, CSAIL This is particularly important because the industry standard for threat detection is typically 100 days. AI2, short for Artificial Intelligence Squared, looks at data to detect suspicious activity. It does so by clustering the data into meaningful patterns and then presents its findings to human analysts who identify which events are actual attacks.

In a new paper, researchers from CSAIL and the machine-learning start-up PatternEx have demonstrated an artificial-intelligence platform called "AI²" that can predict 85% of cyber-attacks, by continuously incorporating input from human experts. To predict attacks, AI² combs through data and detects suspicious activity by clustering the data into meaningful patterns using unsupervised machine-learning. It then presents this activity to human analysts who confirm which events are actual attacks, and incorporates that feedback into its models for the next set of data.

A new artificial intelligence (AI) system being developed at MIT's Computer Science and Artificial Intelligence Laboratory is being trained by researchers to aid humans in identifying potential cyber-attacks. Typically, when trying to pinpoint possible attacks, analysts are required to sift through massive amounts of data to find abnormalities and discrepancies--a method that is time-consuming and tedious. Anchored on the idea that AI never gets tired, the new computer based method means that humans can identify cyber-attacks more efficiently. AI2 for instance--MIT's new system, which honed its ability to identify threats after reviewing three months worth of log data from an unidentified ecommerce platform--can review millions of log lines every day. Once it spots something suspicious, a human can then take over and promptly check for possible signs of a security breach.

Cyber attacks have been in the news a lot lately. From cases of ransomware holding hospital records hostage to the hack that crippled Sony t0 the security breach that left VTech toys vulnerable, a lot of damage can be done if companies don't adequately protect their data. But oftentimes, signs that a system has been compromised are not clear until it's too late. Human analysts may miss the evidence, while automated detection systems tend to generate a lot of false alarms. Cue the rise of artificial intelligence, or at least AI that can work in tandem with human analysts to spot digital clues that could be signs of trouble.

Scientists at Massachusetts Institute of Technology (MIT) claim they have created an AI that can detect 85% of cyber attacks -- albeit with the help of humans. The „AI2" algorithm, developed by MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and machine learning …

An AI created by scientists at the Massachusetts Institute of Technology (MIT) uses machine learning to detect suspicious activity - getting it right 85 per cent of the time. The system uses an algorithm called "AI2", that detects anomalies, in conjunction with a human expert, because AI2 on its own can lead to false positives, according to MIT News. "The more attacks the system detects, the more analyst feedback it receives, which, in turn, improves the accuracy of future predictions," said one of the researchers behind the project, Kalyan Veeramachaneni. "That human-machine interaction creates a beautiful, cascading effect." The merging of artificial intelligence and what researchers call "analyst intuition" has allowed for this new system to be successful in its early development, Veeramachaneni and fellow scientist Ignacio Arnaldo said.

The world has seen numerous major cyber attacks in the past couple of years, with targets ranging from government agencies to health insurers to entertainment companies. A group of scientists at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) are working to create a line of defense against these threats to privacy and security. They've developed an AI that can detect attacks on networks as they happen, 85 percent of the time. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. AI2, short for Artificial Intelligence Squared, looks at data to detect suspicious activity.

The world has seen numerous major cyber attacks in the past couple of years, with targets ranging from government agencies to health insurers to entertainment companies. A group of scientists at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) are working to create a line of defense against these threats to privacy and security. They've developed an AI that can detect attacks on networks as they happen, 85 percent of the time. Our biggest ever edition of TNW Conference is fast approaching! AI2, short for Artificial Intelligence Squared, looks at data to detect suspicious activity.

A new artificial intelligence system developed by researchers at MIT merges human and machine capabilities to hunt potential cyber-attacks and weed out false positives. Called AI2, the platform acts as a virtual analyst and has so far proven its ability to detect 85 percent of attacks. As the system presents its findings to human analysts, feedback is incorporated to continually improve its detection rates. A new artificial intelligence system developed by researchers at MIT merges human and machine capabilities to hunt potential cyber-attacks and weed out false positives. This allows it to detect suspicious activity, which is then presented to the human analysts for confirmation.